Estimating Monthly LLM Costs: The Practical Way

Most teams underestimate LLM costs because they start with tokens and end with confusion. Budget planning becomes easier when you model usage first.

Calculate monthly scenarios

Step 1: Start with DAU, not total users

Budgets follow active usage. Define:

  • DAU (expected adoption)
  • rollout phases (month 1 vs month 3 vs steady state)

Step 2: Model requests per user

Define a realistic baseline and a stress case:

  • Baseline: expected “normal day”
  • Stress: peak usage + novelty effects

Step 3: Define response length bands

You don’t need exact tokens to budget. Use bands:

  • Short (confirmation, simple answers)
  • Medium (explanations, summaries)
  • Long (multi-step reasoning, structured outputs)

Step 4: Compare scenarios and pick a budget guardrail

A useful budget is not a single number. It’s:

  • Base case (what you expect)
  • High case (what can happen)
  • Guardrails (what you must not exceed)

Frequently Asked Questions

Why not just use token math?
Token math is prone to errors and hard to communicate. Usage-based modeling is more intuitive for business stakeholders.
How do I set a “high-case” scenario?
Consider peak traffic days, marketing campaigns, or unexpected heavy usage patterns.
What usage assumptions are reasonable for my use case?
Start with data from similar features or run a pilot. Benchmarks vary by industry.
How do I communicate uncertainty to stakeholders?
Present a range (Base to High) rather than a single point estimate.

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